Method to measure degree and homogeneity of alumina calcination

ABSTRACT

A method for measuring degree and homogeneity of calcination of alumina utilizing an image analysis device equipped with a sensitive camera in a spectral analysis window corresponding to a wavelength range equal to or in the vicinity of visible light. The method includes the steps of mixing alumina under analysis in a liquid wherein the refractive index is, in the wavelength range, between the refractive index of a lightly calcined alumina and the refractive index of a strongly calcined alumina, preparing a slide for observation of the mixture in the image analysis device, the mixture being illuminated by stable polychromatic radiation compatible with the spectral analysis window, receiving an image by the camera and processing a signal resulting in the definition of an image composed of a given number of pixels with three calorimetric components, and statistically processing the pixels using their calorimetric components and determining the calcination degree and the homogeneity of the calcination.

FIELD OF THE INVENTION

The invention relates to an in-process monitoring method of the degreeand homogeneity of alumina calcination.

The majority of technical aluminas involve, in their production process,a calcination step. Said step is determined to define the standardproperties of the powder to be used in numerous applications (polishing,refractory concrete, fine ceramics, etc.). It is known that thecalcination degree is well correlated with the surface area developed bythe calcined alumina and, for the aluminas of interest to us, saidsurface area, measured using the BET method is typically between 0.5 and5 m²/g.

However, numerous applications and some target applications (ceramics,electronics, etc.) show the need for a more detailed analysis of theseproducts, an analysis particularly giving information on the calcinationhomogeneity of the product; it is clear that two aluminas with a BETsurface area equal to 1 m²/g for example but one of which is homogeneousand the other composed of a mixture of two aluminas at 0.5 and 1.5 m²/gwill not have the same applicative properties.

STATE OF THE RELATED ART

During calcination, the alumina grains are converted into crystalliteagglomerates of varying sizes depending on the degree of calcination.

To estimate the calcination degree achieved, it is possible to grind thealumina to the crystallite size and perform a granulometric analysis butthis method is rarely or never used in practice since it is long andincompatible with the implementation of a method.

It is also possible to measure said calcination degree indirectly fromthe surface area developed by the alumina using a conventional method,such as the BET method. This method consists of measuring the quantityof nitrogen adsorbed over the entire surface area developed by thealumina. Said quantity increases with said surface area and the porosityof the grain (however, provided that the pores are open). It is used inproduction but it is long and does not give information on theheterogeneity of the calcination degree of the product.

Of the known analytical methods, image analysis may be used but it givesessentially dimensional information (grain size, shape factor) which isnot correlated with the desired information (degree and homogeneity ofcalcination).

PROBLEM STATEMENT

The applicant tried to incorporate in the implementation of the aluminamanufacturing method means to measure the degree and homogeneity ofcalcination.

Such means must be more rapid than the BET method in evaluating theaverage calcination degree and give information of the heterogeneity ofthe calcination degree of the alumina produced.

SUBJECT OF THE INVENTION

The invention firstly relates to a method to measure the degree andhomogeneity of calcination of alumina comprising the use of an imageanalysis device equipped with a sensitive camera in a spectral analysiswindow corresponding to a wavelength range equal to or in the vicinityof visible light and comprising the following steps:

-   -   a) mixture of the alumina under analysis in a liquid wherein the        refractive index is, in said wavelength range, between the        refractive index of a lightly calcined alumina and the        refractive index of a strongly calcined alumina;    -   b) preparation of a slide for observation of said mixture in        said image analysis device, said mixture being illuminated by        stable polychromatic radiation compatible with said spectral        analysis window;    -   c) reception of the image by the camera and processing of the        signal resulting in the definition of an image composed of a        given number of pixels with three calorimetric components;    -   d) statistical processing of said pixels using their        calorimetric components and used to give the calcination degree        and the homogeneity of the calcination.

Indeed, the applicant started with the assumption that, by choosing tomix the alumina powder in a liquid with a mean refractive index betweenthe extreme indices of a strongly calcined alumina and a lightlycalcined alumina, it set up the best conditions to accentuate thedifferences in responses to a given lighting, typically visible light,and that theses differences in responses could be processed digitallyand statistically to characterise the calcination degree of the aluminaobserved and the homogeneity of the calcination carried out on thealumina.

It obtained very encouraging results which are explained retrospectivelyas follows:

The refractive index of a substance varies as a function of thewavelength of the radiation passing through it. In the visible lightrange, this variation is much more significant for liquids than forsolids. When a solid is immersed in a liquid with the same refractiveindex, no light dispersion or absorption takes place. However, if therefractive indices are different, a dispersion/absorption phenomenon isobserved.

However, it is known that the refractive index of an alumina variesaccording to its degree of calcination. If an alumina immersed in aliquid is observed and if, for a given wavelength, the refractive indexof the alumina and the liquid is not the same, a dispersion/absorptionphenomenon takes place which is conveyed by a varying light intensityresponse.

When a solid, in this case alumina, is dispersed into a very largenumber of particles, the multiple facets are oriented in a randomfashion with reference to the incident ray of light. Therefore, it isnecessary to illuminate a large number of particles to obtain asignificant statistical effect on the reflected (or transmitted) image.

If a polychromatic light—in the visible range for example—is used forillumination, the intensity response will differ according to thewavelength. The processing of the signal received by the camera makes itpossible to obtain a coloured image that can be broken down into amultitude of pixels characterised by three colour components (accordingto the RGB system recommended in 1931 by Compagnie Internationale del'Eclairage CIE, or according to the Lab system (or Hunt system), oraccording to any three-dimensional calorimetric space reference, etc.).

The applicant observed that the colour of each product, expressed inthis way pixel by pixel in a three-dimensional calorimetric space, ischaracteristics of the product observed and that, by transferring thedesired data to a histogram, it is possible to compare said histogram to“stand” histograms of known aluminas wherein the calcination degree canalso be measured using the BET process.

In this approach, two steps make use of polychromatic radiation but thedistinction that can be made between the spectral analysis window of theradiation illuminating the mixture and the visible spectrum used todescribe the result of the processing of the signal received by thecamera is clear.

The spectral analysis window may indeed correspond to the visible lightspectrum but it may also correspond to a more restricted, continuous ordiscontinuous, wavelength range, or a range extended to the infra-redand ultra-violet ranges. The important factor is that the spectralanalysis window is chosen such that the refractive indices of aluminasof varying degrees of calcination remain stable and that the refractiveindex of the liquid varies in this range, said range being sufficientlybroad so that the refractive index of the liquid is between therefractive index lightly calcined alumina and the refractive index of astrongly calcined alumina. In addition, the order of magnitude of thewavelengths must in particular be less than that of the particle size,which makes it necessary to define a spectral analysis window in awavelength range typically between 1000 Å and 10,000 Å, visible light(#4000–7000 Å) being for this reason well suited and enabling easycontrol of the measurement method. To facilitate the presentation, wewill associate the spectral analysis window below with a visible lightwindow and we will use the terms generally used for the observation ofan object illuminated with visible light.

To prepare the observation, the alumina powder under analysis is mixedin a liquid of a given refractive index. As, in visible light, therefractive index of an under-calcined alumina is in the vicinity of 1.70and the refractive index of an alumina α is in the vicinity of 1.76, aliquid with a refractive index in the vicinity of 1.73 is preferentiallychosen. Such liquids, such as methylene iodide, are commerciallyavailable.

The mixture is deposited for example on a glass slide such as those usedin optical microscopy. The slide is then placed in the observation fieldof the camera by means of a magnification system such that each particlecan be represented by a sufficient number of pixels. Typically, with animage of 640*480 pixels, it is preferable to choose a magnification suchthat the image contains less than 1000 particles. However, saidparticles must be sufficient in number, since it is necessary to obtaina significant statistical effect on the image. The magnification systemof an image analysis device used within the scope of the invention mustmake it possible to analyse an image comprising at least 50 particles.

The mixture is illuminated by a stable polychromatic radiationcompatible with the spectral analysis window of the camera, i.e. thewavelength range of the reflected or transmitted radiation is includedin the spectral analysis window of the camera.

The signal detected by the camera is processed such that an imagedefined by a given number of pixels with three calorimetric componentsis obtained. The image may contain a colour corresponding to theradiation detected by the camera but it may also have codified coloursarbitrarily characterising the radiations detected—in this case, theterm “false colours” is used. However, it is preferable to be able touse the entire range of the calorimetric space to define each pixel ofthe image.

The pixels, characterised by the three components or a calorimetricspace, are then processed. Firstly, it is necessary to be certain thatthey correspond to particles since they are not contiguous in themixture prepared on the slide and do not occupy the entire surface areaof the image. Sorting may be carried out easily since the part of theimage corresponding to background, i.e. occupied only by the liquid,shows a high light intensity. Therefore, it is possible to remove allthe pixels wherein the three components are greater than a given value.

The remaining pixels are then represented in the calorimetric space. Asthe calcined alumina observed does not correspond to a perfectlyhomogeneous phase and as each pixel may in fact correspond to aplurality of photons of different energy, therefore to a mixture ofcolours, the representation in the calorimetric space of the pixels ofthe image correspond to a scatter of points varying in range. Theapplicant observed that, by choosing a liquid with a suitablediffractive index for the chosen spectral analysis window, it waspossible to differentiate between aluminas using the scatters of pointsrepresenting said aluminas in the calorimetric space, the location ofsaid scatters being related to their calcination degree and the range ofsaid scatters being related to their degree of homogeneity.

Using these representations in a three-component space, several types ofstatistical processing are possible. The purpose of the processingdescribed here is to obtain a representation that is easier tointerpret. It consists of situating the images under analysis withreference to the representative scatters of two known aluminas which arecalcined at most different possible calcination degrees. For example, anα alumina and an under-calcined alumina, preferentially the leastcalcined but the most homogeneous possible, are chosen.

In principle, the two scatters corresponding to the alpha alumina and tothe under-calcined alumina, respectively, are distinct from each other.Otherwise, it is preferable to choose another liquid and/or anotherspectral analysis window.

If the two scatters are distinct, it is possible to define a sub-spacewhich “passes” through these scatters (an axis or a plane which passesthrough their centres of gravity, for example) and wherein theestimation of the calcination degree may be carried out using the“distances” between points, highlighted in said sub-space. In this way,it is possible to project the scatter of points of the alumina underanalysis onto said sub-space and estimate the distance existing betweensaid projection and that of the α alumina and/or that existing betweensaid projection and that of the under-calcined alumina.

In this way, by illuminating the alumina+liquid mixture with visiblewhite light, it is observed that a particle of α alumina gives a blueimage and an under-calcined alumina gives a brown image of varyingdarkness. If the pixels were defined in the RGB reference system, it isattempted to classify them according to the “B−R” (blue less red)component. By classifying the number of pixels with a rising B−Rcomponent, a histogram or characteristic spectrum is obtained: thehigher the calcination degree of the alumina, the more its spectrum ispositioned to the right and, conversely, the lower the calcinationdegree of an alumina, the more its spectrum is located to the left.

The mean of the histogram obtained is characteristic of the calcinationdegree of the alumina analysed.

The standard deviation of the histogram obtained in this way ischaracteristic of the homogeneity of the calcination of the aluminaanalysed.

Secondly, the invention relates to the use of the measurement methoddescribed above to monitor the degree and homogeneity of calcination ofalumina produced continuously in a ring furnace. Said measurement methodis much more rapid that the BET method in determining the calcinationdegree of the alumina and makes it possible to react more rapidly to adeviation in the parameters of the furnace. This is particularlyadvantageous for a ring furnace working in continuous mode and producingseveral tonnes of alumina an hour. Finally, using this method, which isthe only one known to date that makes it possible to determine thehomogeneity of calcination, it is possible to correct the adverseeffects of dust recycling which takes place in an untimely and poorlycontrolled fashion in ring furnaces and “contaminates” the aluminaproduced with an alumina of different grain size.

Using an alumina sample taken from the furnace, four slides areprepared. Each slide is observed at three different points using theclaimed measurement method. Results that are reproducible to within 5%are obtained.

FIGURES

FIG. 1 illustrates the acquisition chain used within the scope of theexample described below.

FIG. 2 represents three response spectra on the axis (B−R+100) relatingto three aluminas (a, b, c) having different calcination degrees.

FIG. 3 shows the bijective relationship existing between the calcinationindex IC measured using the method according to the invention describedin the example and the BET surface area expressed in m²/g.

FIG. 4 gives the relationship between the BET surface area and thecrystallite size TC expressed in μm.

FIG. 5 shows this relationship in the range most specifically ofinterest to ceramists.

FIG. 6 shows the spectra obtained by mixing two aluminas of differentdegrees of calcination.

FIG. 7 shows, as a function of the percentage of one of the ingredients,the variation of the homogeneity index in a mixture of two aluminas, onestrongly calcined and the other under-calcined.

EMBODIMENT OF THE INVENTION

Acquisition Chain (FIG. 1)

The acquisition chain, represented in FIG. 1, is as follows:

1) The slide A on which the alumina/index liquid mixture is depositedmust be prepared carefully: it is necessary to prevent the appearance ofbubbles and obtain the most homogeneous particle distribution possible,said particles not being attached to each other. We selected a liquidwith an index of 1.73. For industrial calcination monitoring in ringfurnaces, this preparation may be automated.

2) Alumina grains being micronic, the use of a binocular microscope Bwith variable lenses according to the alumina is recommended. The aim isto obtain a sufficient quantity of grains for a valid statisticalanalysis (thus avoiding having to increase the number of tests).

3) The slides are illuminated with visible spectrum light. The settingand stability of the lighting are important since they affect thecalorimetric components of the pixels of the image obtained by thecamera C. It is particularly necessary to avoid saturate light intensitysignals.

In this example, the camera is a mono-CCD matrix camera. A tri-CCDcamera, which is more precise since it makes it possible to obtain thethree basic colours (Red-Green-Blue) separately, is not necessary, butit makes it possible to access more detailed information resulting in areduction in uncertainty on the measurements made with the colourimages.

4) the data processing system D comprising

-   -   a digitisation card used to digitise the information provided by        the camera and offering numerous setting possibilities (colour,        saturation, contrast, luminosity, etc.),    -   the image processing application: it is used to perform        acquisitions with the camera and then process the images in        different formats (RGB, HSL, greyscale, etc.). A        macro-instruction system enables the automatic acquisition        processing operations. We used OPTIMAS.    -   the computer used is sufficiently powerful to process the images        acquired (640*480 pixels*3 components). In this case, the        computer used is a PC with 48 MB RAM.

5) The colour of each product is thus expressed pixel by pixel in athree-dimensional calorimetric space and each shade of colour may betransferred to a histogram using which the desired data may beextracted.

By classifying the pixels according to their components, a spectrum E isdefined by projection on a particularly suitable axis to accentuate thedifferences in response. In this way, according to their degree ofcalcination, the grains appear throughout the axis. The mean of thespectrum can easily be linked with the mean degree of calcination,itself correlated with the BET surface area: in this way, each productrange shows a specific spectrum appearance. In addition, the dispersion(spread of the curve) gives a reliable estimation of the heterogeneityof calcination of each product.

EXAMPLE OF APPLICATION

Chromatic Space Reference System: RGB, the Axis on Which the Spectrum isProjected being the B−R Axis

In this reference system, the greater the blue component of the pixel,the more the corresponding part of the grain is considered to becalcined. Therefore, we calculated for each pixel the difference betweenthe blue component (noted from 0 to 255) and the red component (asabove) and recorded on the axis B−R+100 (difference between bluecomponent and red component+100) the pixel populations corresponding todifference levels grouped in intervals of 10. The histograms obtained inthis way have the same appearance as the characteristic spectra in FIG.2, relating to three aluminas with different calcination degrees.

Alumina a is a metallurgic alumina, subject to light calcination, and asignificant proportional of its grains have a blue component less thanthe red component: they are rather brown in appearance. On the otherhand, alumina c is an alumina calcined in the presence of a mineralisingagent. It comprises a majority of blue grains. Alumina b is anintermediate alumina which comprises a spectrum located between bothextreme spectra. Alumina a, b and c comprise declining BET surface areas(a: 75 m²/g; b: 3.9 m²/g; c: 1.1 m²/g). The products thus appear to beclassified according to their calcination degree or, in reverse order,according to their BET surface area.

It is noted that some peaks are characteristics of the alumina family:

-   -   peak at 60: under-calcined grains,    -   peak at 180: calcined grains.        Determination of Calcination Index

On the basis of spectra such as those in FIG. 2, it is possible todetermine a calcination index IC;

-   -   If i is the classes from 0 to 260 (interval of 10), f_(i) is the        percentage and c_(i) the value of the difference (blue        component−red component+100) corresponding to each class i, the        calcination index is defined by:        ${IC} = \frac{\sum\limits_{i = 0}^{i = 260}\;{{fi}*{ci}}}{100}$

For all the products, a bijective correspondence between the calcinationindex IC and the BET values (FIG. 3) is found.

FIG. 4 shows a correlation conventionally defined between the BETsurface area and the crystallite size TC—characterised here by the finediameter d50 obtained by means of granulometry after grinding—in therange of interest to ceramists and refractory scientists (0.8 to 5m2/g). This correlation is of the type:BET=A/(TC−L)+B

-   -   where B (of the order of 0.5 m2/g) represents the analytical        limit of the BET measurement and where L (of the order of 0.4        μm) represents analytical limit of the granulometric        measurement.

Therefore, it is possible to correlate the calcination index IC with thecrystallite size TC and, in the range of interest to ceramists andrefractory scientists a linear equation: TC=A′·IC+B′ (FIG. 5) isobtained. Such an equation is refined for each product range.

Determination of Homogeneity Index

The spectra of some products undergo more spreading than others andcomprise varied grain colours. The homogeneity index was defined toaccount for the spreading and dispersion of such curves. The standarddeviation of the frequencies was selected for one product family.

To illustrate the representative nature of this index, we prepared twoproducts in the laboratory: one calcined (BET=1.4 m²/g) and oneunder-calcined (BET=77 m²/g) that we mixed. The first (corresponding to“100% alpha” in FIG. 6) has a confined curve, the second (correspondingto “0% alpha” in FIG. 6) is more dispersed. The spectra obtained ondifferent mixtures (corresponding to “x % alpha”, where x issuccessively equal to 95, 90, 85, 80, 60 and 40) are presented in FIG.6.

FIG. 7 shows, as a function of the percentage of calcined alumina(symbolised by “% alpha”), the variation in the homogeneity index IH ofthe different mixtures obtained. Note that any mixture comprising up to70% calcined alumina has a lower homogeneity index than that ofunder-calcined alumina.

Advantages of the Method According to the Invention

-   -   rapid and reliable response    -   measurement method can be integrated into monitoring of calcined        alumina production; in practical terms, the preparation of the        sample requires some training but the determination of the        coefficients IC and IH is automatic, enabling the operator to        react rapidly in the event of a deviation in production        parameters. This more rapid action has two beneficial effects:        greater furnace flexibility and improved stability of        calcination conditions. In this way, it is possible to gain 20%        on out of specification products.

1. Method for measuring degree and homogeneity of calcination of aluminautilizing an image analysis device equipped with a sensitive camera in aspectral analysis window corresponding to a wavelength range equal to orin the vicinity of visible light and comprising the steps of: a) mixingalumina under analysis in a liquid wherein the refractive index is, insaid wavelength range, between the refractive index of a lightlycalcined alumina and the refractive index of a strongly calcinedalumina; b) preparing a slide for observation of said mixture in saidimage analysis device, said mixture being illuminated by stablepolychromatic radiation compatible with said spectral analysis window;c) receiving an image by the camera and processing a signal resulting inthe definition of an image composed of a given number of pixels withthree calorimetric components; and d) statistically processing saidpixels using their calorimetric components and determining thecalcination degree and the homogeneity of the calcination.
 2. Methodaccording to claim 1 wherein the spectral analysis window of the camerais the visible spectrum and wherein the refractive index of the liquidis chosen between 1.70 and 1.76.
 3. Method according to claim 1 whereinthe image analysis device comprises a magnification system such that itmakes it possible to obtain images of said mixture containing between 50and 1000 particles.
 4. Method according to claim 1 wherein the imagesare defined by pixels with three RGB calorimetric components.
 5. Methodaccording to claim 4 wherein the pixels are classified according to a“B−R” (blue less red) component, a histogram obtained in this way havinga mean and a standard deviation characteristic of the degree andhomogeneity of calcination of the alumina observed in this way,respectively.
 6. In a process for producing calcined alumina comprisingsampling the calcined alumina to determine degree and homogeneity ofcalcination, the improvement comprising measuring the degree andhomogeneity of the calcination utilizing an image analysis deviceequipped with a sensitive camera in a spectral analysis windowcorresponding to a wavelength range equal to or in the vicinity ofvisible light and comprising the steps of: a) mixing alumina underanalysis in a liquid wherein the refractive index is, in said wavelengthrange, between the refractive index of a lightly calcined alumina andthe refractive index of a strongly calcined alumina; b) preparing aslide for observation of said mixture in said image analysis device,said mixture being illuminated by stable polychromatic radiationcompatible with said spectral analysis window; c) receiving an image bythe camera and processing a signal resulting in the definition of animage composed of a given number of pixels with three calorimetriccomponents; and d) statistically processing said pixels using theircalorimetric components and determining the calcination degree and thehomogeneity of the calcination.